DC motor

Algorithm

Control (management)

Discretization

Rotor (electric)

Engineering

Biology

Optimization algorithm

Control engineering

Gray wolf

Weighting

Computer science

Mathematical optimization

Penalty method

Gray (unit)

Radiology

Paleontology

Mechanical engineering

Mathematics

Noise shaping

Feed forward

Electronic engineering

Mathematical analysis

Canis

Artificial intelligence

Medicine

Control theory (sociology)

Dither

Electrical engineering

IEEE Transactions on Power Electronics

This paper presents an optimal control strategy for a permanent-magnet synchronous hub motor (PMSHM) drive using the state feedback control method plus the gray wolf optimization (GWO) algorithm. First, the linearized PMSHM mathematical model is obtained by voltage feedforward compensation. Second, to acquire satisfactory dynamics of speed response and zero d-axis current, the discretized state-space model of the PMSHM is augmented with the integral of rotor speed error and integral of d-axis current error. Then, the GWO algorithm is employed to acquire the weighting matrices Q and R in linear quadratic regulator optimization process. Moreover, a penalty term is introduced to the fitness index to suppress overshoots effectively. Finally, comparisons among the GWO-based state feedback controller (SFC) with and without the penalty term, the conventional SFC, and the genetic algorithm enhanced proportional-integral controllers are conducted in both simulations and experiments. The comparison results show the superiority of the proposed SFC with the penalty term in fast response.

State Feedback Control for a PM Hub Motor Based on Gray Wolf Optimization Algorithm